Systems dealing with spread spectrum signals for code division multiple access (CDMA), in which a plurality of signals are transmitted in the same band, are subject to inter-signal interference that is generated in dependence on the correlation among codes assigned to individual signals. The characteristics or quality of the signals are deteriorated increasingly with increasing number of signals involved. In addition, signal level fluctuations result in increased interference of higher level signals on lower level signals, thus greatly reducing the characteristics of the lower level signals.
Some methods for improving signal characteristics by reducing such inter-signal interference have been proposed. One such method is realized by a system called decorrelation system. In this system, decorrelation is made by using known code correlations. FIG. 19 shows an example of the circuit construction which realizes this system. Referring to the figure, designated at 1001 to 100K are correlators, and at 101 is a decorrelator.
As a spectrum spreading scheme, a direct sequence (DS) system is assumed. A received signal r is expressed by formula (1) in FIG. 23.
In the formula (1), K represents the number of simultaneously transmitted signals, dk a k-th (k=1, 2, . . . , K) transmitted symbol, C.sub.k the spreading code of a k-th signal, c.sub.k a despreading operation caused by spreading code c.sub.k, n background noise introduced into signal on the transmission line, and a.sub.k a reception level.
The rule of formula (2) in the same figure is met when the despreading operation c.sub.k and the correlating operation c.sub.k are synchronized to each other.
The correlating operation c.sub.k is completed after one symbol has been transmitted, and this is expressed by the provision of a delay element z for one symbol.
With the received signal r, the k-th correlator 100K provides an output d.sub.k, which is given by formula (3) in the same figure.
Formula (4) in the same figure is a vector expression of all the signals to be demodulated in a single form. In the formula (4), C is a matrix type operator corresponding to a correlation matrix.
For the sake of brevity, it is assumed that the symbol timings of the signals are synchronized, and denoting the correlation between signals i (i=1, 2, . . . , K) and signals j (j=1, 2, . . . , K) by ci, j (ci, i=1, .vertline.ci, j.vertline..ltoreq.1) we can use formula (5) in the same figure, where the matrix C of the elements ci, j represents the correlation of signals.
The decorrelator 101 obtains an inverse matrix (C.sup.-1) to the correlation matrix C, and executes matrix multiplification on the outputs of the correlators 1001 to 100K as in formula (6) in the same figure.
Since the spreading codes of the individual signals are known, the elements ci,j of the correlation matrix C can be calculated in advance, and the inverse matrix (C.sup.-1) can be obtained in advance.
It will be seen that by substituting the formula (5) into the formula (6) the signal d.sup.(.infin.) obtained by the above decorrelation can be expressed by formula (7) in the same figure.
This means that the decorrelated signal d.sup.(.infin.) comprises the product of the reception level A of the original signal and the transmitted symbol d and noise component n that is introduced, and is not affected by the other signals that are simultaneously received. In other words, it is meant that inter-signal interference is cancelled, and that interference cancelled detected signals (or detected signals with cancelled interference) can be obtained. The interference cancelled detected signals can be demodulated through phase synchronization, for instance, and bit determination.
While the operation of the decorrelation system in the case of presence of symbol synchronization has been shown, in the case of absence of the symbol synchronization (asynchronous case) the decorrelation is obtainable as well, as shown in "Near-Far Resistance of Multiuser Detectors in Asynchronous Channels" (E. Lupas S. Verdu, IEEE Trans. Com. Vol. 38, No. 4, April 1990). Denoting the number of symbols transmitted in a sufficiently long time by L, it can be considered that LK synchronized signals are transmitted during this time. This means that the decorrelation in the asynchronous case can be attained by dealing with the correlation matrix C having a magnitude of LK.times.LK.
In the decorrelation system, a change in the number of signals causes a change in the size of the correlation matrix C, thus making it necessary to compute again the inverse matrix (C.sup.-1) used for the decorrelation process. In other words, in such case as when signals are frequently turned on and off by voice activation or the like or when delay times are changed quickly in mobile communication, the inverse matrix computation should be made in a very short period of time.
The inverse matrix computation generally requires a computational effort which is proportional to the cube of the matrix size. Specifically, the computational effort is proportional to about the cube of K in the case of presence of the symbol synchronization and to about the cube of LK in the asynchronous case. This means that it is difficult to make the inverse matrix computation on the real time basis.
Aside from the decorrelation system, a replica signal cancellation system has been proposed as another system for improving signal characteristics by cancelling inter-signal interference. In this system, replica signals of individual signals are produced and subtracted from the originally received signal for the interference reduction. The replica signals of the individual signals may be subtracted either one by one (serial system) or collectively (parallel system) from the original signal in FIGS. 20 and 21 show examples of the constructions of the serial system (or also called successive system) and the parallel system, respectively.
The illustrated systems are for the case where the number of signals is K. Re-modulators 1291 to 129K generate replica signals by re-spreading symbols detected in correlators 1191 to 119K. Replica signal cancellers 1491 to 149K subtract the replica signals of the other stations either one by one or collectively from the original signal (i.e., received signal), and correlators 1591 to 159K again detect symbols. The interference cancellers 2791, 2792 and also the interference cancellers 2891, 2892 are identical or alike in construction. A plurality of such interference cancellers are connected such as to iteratedly carry out signal processing with the re-modulators, replica signal cancellers and correlators shown above. In either of the above systems (i.e., serial and parallel systems), the replica signals are generated either by a method, in which the symbols detected by the correlators are re-spreaded while holding their intensity (soft decision basis), or by a method, in which the symbols detected by the correlators are once subjected to bit determination (hard decision basis), then re-spreaded, and then multiplied by the reception levels of the individual signals to restore the signal intensity.
The serial system has a problem that the signal first demodulated by the correlator 1191 is not interference cancelled. To avoid this problem, a method is adopted, in which the highest intensity signal is demodulated first, and the lowest intensity signal is demodulated finally, thereby improving the overall demodulation performance. Where no means for detecting the intensity of the individual signals is provided, the signals are ranked with respect to some reference by using some substitute means, and the demodulation order is determined according to this ranking. However, such a scheme where the demodulation order is varied in dependence on the ranking, is subject to circuit scale increases, that is, subject to new structural problems that are posed when structural problems are to be solved.
The parallel system is superior in the interference cancellation property to the serial system in the case where the reception intensity levels of the individual signals are equal or close to one another. In the case where the individual signal intensity levels vary greatly under fading circumstances or due to the near-far problem, however, the serial system is superior in the interference cancellation property. These technical affairs are detailed in A. Duel-Hallen, J. Holtzman, and Z. Zvonar, "Multiuser Detection for CDMA System", IEEE Personal Communications, April 1995. The parallel system has a further problem that when the ratio between the number K of signals to be demodulated and the spreading factor exceeds a certain value, the demodulation performance is rather deteriorated with increasing number of interference canceller stages. Due to this problem, only demodulation performance in cases where the ratio of the number K of signals to be demodulated and the spreading factor is at most around 0.5 and also the interference cancellation is done in a double of stages, are reported in prior art literatures. For example, according to the above literature the interference cancellation is done in up to two stages, and according to Y. Yoon, R. Kohno et al, "A Spread-Spectrum Multi-Access System with a Co-Channel Interference Canceller for Multipath Fading Channels", IEEE JSAC December 1993, it is up to three stages.
An interference canceller proposed in Japanese Laid-Open Patent Publication No. 7-131382 (U.S. Pat. No. 5,467,368) is a parallel system variety, which is realized with a construction as shown in FIG. 22. Referring to the figure, re-modulators 1291 to 129K generate replica signals by re-spreading symbols detected by correlators 1191 to 119K. A replica signal canceller 1490 collectively subtracts all the replica signals from the originally received signal. Symbols detected by correlators 1591 to 159K are added to symbols detected again by the correlators 1191 to 119K. The interference cancellers 2991, 2992, . . . are identical or alike in construction.
The operation of the above system shown in FIG. 22 will now be described. Since each of the outputs of the correlators 119k (k=1, 2, . . . K) is given by the formula (3), a k-th replica signal obtained from the re-modulator 129k is as given by formula (8) in FIG. 24.
The replica signal canceller 1490 which subtracts all the replica signals from the received signal, provides a signal as given by formula (9) in the same figure.
The output signal of the replica signal canceller 1490 is inputted to the correlators 1591 to 159K, which take the correlations between the individual input signals and the corresponding spreading codes. Then, the symbols detected by the correlators 1191 to 119K are added to the symbols detected by the correlators 1591 to 159K. Each resultant sum symbol d.sub.k.sup.(1), i.e., k-th output symbol from the interference canceller 2991, can be expressed by formula (10) in the same figure.
Using vector expression for only K signals, the above formula is reduced to formula (11) in the same figure.
In the formula (11), I represents an identity matrix.
When the process in the re-modulators 1291 to 129K through the correlators 1591 to 159K is executed iteratedly M times, a signal d.sup.(M) given by formula (12) in the same figure is obtained.
On the right side of the formula (12), d represents the signal detected by the correlators 1191 to 119K, and is given by the formula (4). The formula (4) can be replaced with formula (13).
By substituting the formula (13) into the formula (12), it will be seen that the signal d.sup.(M) obtained in the case (where M interference canceller stages are provided) is given by formula (14) in the same figure.
In the above formula, the right side first term represents the product of the reception level A of the original signal and the transmitted symbol d, that is, a desired signal component to be detected. The second term on the same side represents a value which raises the correlation matrix to the Mth power (M is the number of interference canceller stages), that is, a residual interference component. This indicates that provided the correlation matrix C meets the condition of formula (15) in the same figure, the interference component is reduced with increasing number of interference canceller stages.
An extraction way of symbol timings of signals to be demodulated will be described as follows. Correlations of received signal without being interference cancelled and spreading codes assigned to individual spread spectrum signals are detected using matched filters, and the symbol timings are determined according to the detected peak timings.
Utilizing the effect of the interference cancellation to improve the link quality, permits accommodating many signals in the same band until a constant quality is met. By increasing the number of signals capable of being accommodated by having resort to the interference cancellation effect, however, the magnitude of the cross-correlation is increased to deteriorate the accuracy of the symbol timings extracted from the received signal. In other words, replica signals which are generated according to symbol timings of reduced accuracy, are erroneous and disable normal interference cancellation, thus deteriorating the demodulation performance. Symbol timing extraction methods which are based on such interference cancellation have been hardly investigated.
The decorrelation system, on the other hand, permits perfectly interference cancelled detected signals to be obtained as described before. However, the system requires inverse matrix computation of a correlation matrix whose size is very large, the computation requiring enormous computational effort and being difficult to realize on real time.
The replica signal cancellation in the prior art, can be realized with far less processing effort compared to the decorrelation.
This method, however, is directly affected by correlation between spreading codes. That is, influence of interference signal appears in the output of the correlator 119K, so that the replica signal generated by the re-modulator 129K contains an error due to the influence of the interference. The error is accumulated as the replica signal cancellation is repeated, and eventually exceeds the desired signal power to be detected. It will be seen that a limitation is imposed on the interference cancellation capacity, and continuously increasing the number of interference canceller stages eventually results in demodulation performance deterioration.
The interference cancellation system proposed in the Japanese Laid-Open Patent Publication No. 7-131382 (U.S. Pat. No. 5,467,368) is a sort of replica signal cancellation system, in which a plurality of replica signals are generated in parallel for cancellation from the original received signal. When soft decision is adopted to generate the replica signals, the resultant output signal is close to that in the decorrelation system. In other words, excellent performance can be ensured with the same order of processing effort as in the replica signal cancellation system.
Again in this system, however, under a particular condition replica signal errors due to correlation between spreading codes are accumulated with increasing number of stages and eventually exceed the desired signal power to be detected. The condition is governed by the correlation received by a signal from a (K-1)-th signal. For example, with a correlation magnitude of about 0.5, the mean performance is slightly improved up to the third stage, but with further stage number increase it turns to be deteriorated and is eventually sharply deteriorated.